Data Architect / Modeler – Databricks
About the Role
The Data Architect / Modeler works closely with business stakeholders, data owners, and application teams to translate business and data requirements into clear, implementable target-state data models and designs on Databricks. This role bridges business understanding and technical execution — ensuring data architecture is consistent, scalable, and aligned with enterprise data strategy.
Key Responsibilities
- Define and maintain conceptual, logical, and physical data models aligned with Databricks lakehouse architecture
- Translate business requirements, data definitions, and business rules into structured data models and implementable designs
- Analyze existing source systems, data structures, relationships, and dependencies to inform target-state architecture
- Design data models leveraging Databricks Unity Catalog, Delta Lake, and medallion architecture patterns
- Define and apply data architecture standards, patterns, and reusable approaches across delivery programmes
- Work closely with engineering teams to ensure data models are technically feasible and implementable on Databricks
- Identify and resolve data architecture and modelling gaps across business domains
- Support data standardization, metadata management, lineage, and data quality considerations in target designs
- Maintain traceability between business requirements and resulting target data structures
- Provide hands-on guidance to delivery teams and contribute to continuous improvement of data architecture practices
Required Qualifications
- 5+ years hands-on experience in data architecture and data modelling
- Strong experience translating business requirements into logical and physical data models
- Hands-on experience with Databricks platform — Delta Lake, Unity Catalog, medallion architecture patterns
- Experience with data architecture standards, patterns, and enterprise data design principles
- Proficiency with data modelling tools and notation (ERD, UML, dimensional modelling)
- Experience with data governance, metadata management, and data lineage
- Strong communication skills with technical and business audiences
- Bachelor’s degree in Computer Science, Engineering, or related field
Good to Have:
- Experience designing and implementing data models on Databricks lakehouse platforms
- Expertise with Delta Lake optimization, partitioning strategies, and performance tuning
- Experience with Databricks SQL, Spark SQL, and data transformation on Databricks
- Complex banking data and financial services data models
- Large-scale data transformation or migration programmes on cloud platforms
- Experience with dimensional modelling, normalized schema design, or data vault methodology
- Familiarity with data quality frameworks and data lineage tools (e.g., OpenMetadata)
- Experience with Agile delivery and iterative data architecture design
- Master’s degree or advanced certifications in data architecture
Singapore
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